Search engines form the core of discovery of research these days. There’s just too much information out there to search journal by journal or on a manual basis.
We highlighted in a previous post the advantages of using ScienceOpen’s dual-layered search and filter functions over others like Google Scholar. Today, we’re happy to announce that we just made it even better!
Say you want to search all of PeerJ’s content. Pop ‘PeerJ’ into the journal search, and it’ll come up with all their content, as it’s all indexed in PubMed. Hey presto, there you have 1530 papers, all with full texts attached. Neat eh! And that will update as more gets published with PeerJ, so you know what to do.
But that’s a lot of content. What you’ve just discovered is the PeerJ megajournal haystack. We want to filter out the needles.
Continue reading “Pimp my search engine”
The amount of published scientific research is simply enormous. Current estimates are over 70 million individual research articles, with around 2 million more being published every year. We are in the midst of an information revolution, with the World Wide Web offering rapid, structured and practical distribution of knowledge. But for researchers, this creates the monolith task of manually finding relevant content to fuel their work, and begs the question, are we doing the best we can to leverage this knowledge?
There are already several well-established searchable archives, scientific databases representing warehouses for all of our knowledge and data. The most well-known include the Web of Science, Scopus, PubMed, and Google Scholar, which together are the de facto mode for current methods of information retrieval. The first two of these are paid services, and attempts to replicate searches between all platforms produce inconsistent results (e.g., Bakkalbasi et al., Kulkarni et al.), raising questions about each of their methods of procurement. The search algorithms for each are also fairly opaque, and the relative reliability of each is quite uncertain. Each of them, though, have their own benefits and pitfalls, which are far better discussed elsewhere (e.g. Falagas et al.).
So where does this leave discoverability for researchers in a world that is becoming more and more ‘open’?
Continue reading “Moving beyond a journal-based filtering system”